2 edition of Capacity constrained multi-facility dynamic lot-size problem found in the catalog.
Capacity constrained multi-facility dynamic lot-size problem
by Katholieke Universiteit Leuven, Faculteit der Economische en Toegepaste Economische Wetenschappen in [Leuven]
Written in English
|Series||Katholieke Universiteit Leuven, Faculteit der Economische en Toegepaste Economische Wetenschappen ;, nr. 19, Reeks van de Faculteit der Economische en Toegepaste Economische Wetenschappen ;, nieuwe reeks, nr. 19.|
|LC Classifications||TS155.8 .L36 1976|
|The Physical Object|
|Pagination||158 leaves :|
|Number of Pages||158|
|LC Control Number||82211567|
Project Management and Senior Design II. For the Love of Physics - Walter Lewin - - Duration: Lectures by Walter Lewin. Yu, Chen, and Zhang: Dynamic Capacity Management with General Upgrading 2 Article submitted to Operations Research; manuscript no. (Please, provide the mansucript number!) demand. This paper studies the in uential practice of upgrading, where higher-quality products can be used to satisfy demand for a lower-quality product that is sold out.
A forward algorithm for a solution to the following dynamic version of the economic lot size model is given: allowing the possibility of demands for a single item, inventory holding charges, and setup costs to vary over N periods, we desire a minimum total cost inventory management scheme which satisfies known demand in every period. Disjoint planning horizons are shown to be possible which Cited by: Abstract. Uncertainty associated with managing the dynamic capacity in changeable manufacturing is the main source of its complexity. A system dynamics approach to model and analyze the operational complexity of dynamic capacity in multi-stage production is by: 3.
Chapter 7: Capacity and Constraint Management 1. C APACITY 1. Capacity 1. The throughput, or the number of units a facility can hold, receive, store, or produce in a period of time 2. Three time horizons: short, intermediate, and long 3. Capacity decisions must be integrated into the organization’s mission and strategy 4. Investments are not to be made as isolated expenditures. Capacity Planning Capacity planning is a long-term strategic decision that establishes a firm's overall level of resources. It extends over a time horizon long enough to obtain those resources--usually a year or more for building new facilities or acquiring new businesses. Capacity decisions affectFile Size: KB.
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(5) i Henceforth, we shall assume that (5) is satisfied. Lambreet~t, J. Vander Eecken / A capacity constrained single-facility dy~tami: lot-size model The constraints (2)-(4) define a closed bounded convex set, and since F is concave we know that Cited by: A computationally efficient algorithm for a multi-period single commodity production planning problem with capacity constraints is developed.
The model differs from earlier well-known studies involving concave cost functions in the introduction of production capacity constraints which need not be equal in every by: (). The Dynamic Lot-Sizing Problem for Multiple Items Under Limited Capacity.
A I I E Transactions: Vol. 13, No. 4, pp. Cited by: Vander Eecken / A facilities in series capacity constrained dynamic lot-size model 45 4. Solution algorithms Two procedures will be discussed.
Solution by means era series of Zangwill models Suppose there are n possible production plans for the last facility satisfying Theorem Cited by: Download PDF: Sorry, we are unable to provide the full text but you may find it at the following location(s): (external link)Author: Marc Lambrecht.
A Dynamic Lot Sizing Algorithm with Capacity Constraints P. Eisenhut IBM System Products Division, East Fishkill Facility, Hopewell Junction, New York, Pages Cited by: The models used for calculation of lot sizes are a dynamic programming approach presented by Bomberger () and a heuristic method presented by Segerstedt ().
The two models are further presented in subsequent sections. We consider N items which are produced, one at a time, on a capacity constrained machine.
We use the following notations:Cited by: The Jit gospel. Article (PDF Professor Schonberger summarizes his book of the same title (published by The Free Press in ).
Capacity constrained multi-facility dynamic lot-size problem. An Algorithm for the Dynamic Lot-Size Problem with Time-Varying Production Capacity Constraints. Mgmt. DORSEY, R. C., T. HODGSON AND H. RATLIFF. A Network Approach to a Multi-Facility, Multi-Product Production Scheduling Problem, without Backordering.
M., AND J. VANDER EECKEN. A Facilities in Series Capacity Author: C GravesStephen. Transportation capacity issues are complex because of the multiple dimensions and the integrated nature of transportation systems. In addition, the public sector has a very large and multifaceted impact on transportation capacity.
The following are among the ways to address capacity problems, according to Ailawadi and Santish : •. The uncapacitated lot-sizing problem with sales and safety stocks Article (PDF Available) in Mathematical Programming 89() January with Reads How we measure 'reads'.
Capacitated Dynamic Lot Sizing with Capacity Acquisition Hongyan Li Aarhus School of Business Aarhus University, Denmark [email protected] Joern Meissner Lancaster University Management School, UK [email protected] November 3, Abstract One of the fundamental problems in operations management is to determine the op-timal investment in capacity.
A capacity constraint is a factor that prevents a business from achieving more output. These include minor bottlenecks and constrained capital, designs and resources.
The following are illustrative examples of a capacity constraint. Dynamic Lot Size Problem with Multiple Customers: Customer-Speciﬂc Shipping and Backlogging Costs production capacity limitation, learning in set-ups, perishability, and lost sales. is the non-negativity constraint. The objective of our problem is to minimize the File Size: KB.
In this article, we study deterministic dynamic lot‐sizing problems with a service‐level constraint on the total number of periods in which backlogs can occur over a finite planning horizon. CHAPTER 3 CAPACITY CONSTRAINTS The capacity constraints insure that each plant’s generation does not exceed the properly derated installed capacity for the day types in the model.
This chapter will be organized by type of facility, considering the capacity constraints in sequence of (a) old thermal sites, (b) old hydro sites, (c) new thermal File Size: KB. DOI: / We consider two multi-product dynamic lot size models with one-way substitution, where the products can be indexed such that a lower-index product may be used to.
A new characterization for the dynamic lot size problem with bounded inventory Article in Computers & Operations Research 30(3) March with 45 Reads How we measure 'reads'. Guide to Evaluating Capacity Development Results A collection of guidance notes to help development practitioners and evaluators assess capacity development efforts Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized.
File Size: 2MB. The problem considered is that of scheduling the production of several different items over the same facility on a repetitive basis. The facility is such that only one item can be produced at a time; there is a setup cost and a setup time associated with producing each item; the demand rate for each item is known and constant over an infinite planning horizon, and all demand must be by:.
Abstract. Lot sizing certainly belongs to the most established production planning problems. First scientific reports of this subject date from the beginning of the 20th century and at least one chapter about lot sizing can be found in almost every good textbook about production research by: 1.
This is the capacity constrained resource (CCR) or the Drum that dictates the throughput for the total process. In planning, the CCR must be utilised to its maximum. The release of materials or orders to all parts of the operation (the Rope) should be at the same rate as the Drum is scheduled, because that is all the system can accommodate.Using operations research integer programming techniques, the following is the optimization model to optimize the frit-sealing capacity expansion problem: Subject to constraints: L = 30 m – There is no space available to increase the furnace length for further capacity expansion.